Marketing

Marketing can be summarized as reaching the customer with the right offer, the right message, at the right time, through the right channel while constantly learning. For each step, AI provides an edge to smart marketers:

1- Optimize Product, Pricing & Placement

Gesture Control: Gesture control enables higher levels of activity and engagement by allowing users another mode of interaction with your digital products. Quantify the gesture levels and other engagements in order to provide meaningful insights.

Pricing Optimization: Also called dynamic pricing or demand pricing, pricing optimization allows companies to optimize markdowns. Optimal markdowns minimize cannibalization while maximizing revenues. One of the easiest transformations a business can achieve, dynamic prices directly impact the bottom line and can be rolled out in a matter of days. Optimize markdowns to minimize cannibalization while maximizing revenues.

Physical placement

Merchandising Optimization: Leverage machine learning and big data to optimize your online or offline merchandising. Identify which products are of significant importance for customers. Develop similar products for up-selling and cross-selling.

Shelf Audit/Analytics: Use video, images or robots in the retail area to audit and analyze your use of shelf space. Place your product in the right place. Gain further insights regarding which shelves to perform better. Identify and manage suboptimal performing shelf spaces.

Website Personalization: Personalize your website based on customer data. Provide them with the right products displayed on the main focus points of the page. Provide them with their own color preferences, geographic location details. Seamless integration of their data into your website’s overall attractiveness.

2- Personalize recommendations

A company with an attractive value proposition in the market can still not have much progress if it is offering the wrong product. Personalizing offers allows marketers to match their offers with the right customers.

Recommendation Personalization: Also called recommendation engine or recommendation system, these systems ensure you make the right offer taking into account all

This data is leveraged to retain and upgrade customers with personalized recommendations via email, site search or other channels.

3- Optimize marketing communication

An optimized marketing communication reaches customers at the right time at the right channel with the right message. There are numerous emerging AI companies specializing in these areas. For example, companies like Appzen track customers’ cross-device behavior to ensure that your messages target customers at the device they are using at the time of your marketing communication.

Just a few years ago most messages to customers were hand crafted for specific macro-segments. Today companies like Phrasee suggest personalized messages to ensure that customers receive messages they prefer to read.

Context-Aware Marketing: Context is crucial to marketing. Consider these advertising experiences: You watch a video of a plane crash interrupted by an airline ad. You are reading about a specific phone model exploding when overcharged and you see the ad for that model on the same page. There are horrible yet relatively innocent examples. There has been numerous cases when brand ads were shown in-between videos of hate-groups. Context-aware advertising companies leverage machine vision and Natural Language Processing (NLP) to understand the context where your ads will be served. Protect your brand and increase marketing efficiency by ensuring your message resonates with its context.

Omnichannel: Personalize your marketing communication across different paid marketing platforms. Create a coherent strategy for the overall marketing strategy. Analyze comparatively the impact of your efforts on different platforms.

Retargeting: Retarget customers who have already expressed interest in your products or services. Increase your sales by engaging the right customer.

Channel specific optimizations

Mobile Marketing: Personalized, individual messaging based on each customer’s real-time and historical behaviors. Most of the users are active in mobile platforms, develop your strategy in order to gain a greater share in mobile traffic.

Email Marketing: Emails that are tailored to individual behavior. Detect which email type performs better with your product and customer. Customize by including the necessary email structure and images.

Video Commerce: Auto identify products in videos generated by you or users. Make videos with embedded products shoppable by inserting relevant links.

Advocacy and Loyalty Marketing: Using advocacy system and referrals to introduce and create a customer base via personal connections. Leverage the power of connections by providing the right referral campaign. Estimate the possible sales figures in your marketing strategy by using the impact profile of your customers.

Content Generation: Choose the topic for your content marketing, power it with proprietary data feeds and let AI create unique content. Rather than spending hours for the content, automatic content generation will provide you with the right tools.

4- Connect & leverage customer feedback

Social Media Optimization: Leverage machine learning to optimize the channel, target audience, message and timing of your social media posts.

Social Analytics & Automation: Leverage Natural Language Processing and machine vision to analyze and act upon all content generated by your actual or potential customers on social media, surveys, and reviews.

Social Media Monitoring: Leverage machine learning & natural language processing to monitor social media to make real-time business decisions. Analyze the momentum and emerging trends in your customers for product development or marketing campaign.

Emotion Recognition: Capture the emotional state of your customer by analyzing micro gestures and mimics. Computer vision will help you to capture the details and provide you with the real emotions of your customer.

Predictive sales/lead scoring: Use Artificial Intelligence to enable predictive sales. Score leads and prioritize sales rep actions based on lead scores and contact factors. Sales forecasting is automated with increased accuracy thanks to systems’ granular access to lead scores and sales rep performance. To score leads, these systems leverage anonymized transaction data from their customers, sales data of this specific customer. To assess contact factors these systems leverage anonymized data and analyze all customer contacts such as email and calls.

Sales Rep Chat/ Email Bot: Chatbots are ideal to answer first customer questions. if the chatbot decides that it can not effectively serve the customer, it can pass those customers to human agents. Let 24/7 functioning, intelligent, self-improving bots handle making initial contacts to leads. High value, responsive leads will be called by live agents increasing sales effectiveness.

Sales Rep Response Suggestions: AI will suggest responses during live conversations or written messages with leads. Bots will listen in on agents’ calls suggesting best practice answers to improve sales effectiveness

Sales Rep Next Action Suggestions: Your sales reps actions and leads will be analyzed to suggest the next best action. This situation wise solution will help your representatives to find the right way to deal with the issue. Historical data and profile of the agent will help you to achieve higher results. All leading to more customer satisfaction.

Sales Content Personalization and Analytics: Preferences and browsing behavior of high priority leads are analyzed to match them with the right content, aimed to answer their most important questions. Personalize your sales content and analyze its effectiveness allowing continuous improvement.

Retail Sales Bot: Use bots on your retail floor to answer customer’s questions and promote products. Engage with the right customer by analyzing the profile. Computer vision will help you to provide the right action depending on the characteristics and mimics of the customer.

Prescriptive Sales: Most sales processes exist in the mind of your sales reps. Sales reps interact with customers based on their different habits and observations. Prescriptive sales systems prescribe the content, interaction channel, frequency, price based on data on similar customers.

Sales Call Analytics: Advanced analytics on call data to uncover insights to increase sales effectiveness. See how well your conversation flow performs. Integrating data on calls will help you to identify the performance of each component in your sales funnels.

Sales attribution: Leverage big data to attribute sales to marketing and sales efforts accurately. See which step of your sales funnel performs better. Pinpoint the low performing part by the insights provided by analysis.

Sales Compensation: Determine the right compensation levels for your sales personnel. Decide on the right incentive mechanism for the sales representatives. By using the sales data, provide objective measures and continuously increase your sales representatives performance.

Analytics

Generalist solutions

Analytics Services: Satisfy your custom analytics needs with these e2e solution providers. Vendors are there to help you with your business objectives by providing turnkey solutions.

Specialized solutions

Geo-Analytics Platform: Enables analysis of granular satellite imagery for predictions. Leverage spatial data for your business goals. Capture the changes in any landscape on the fly.

Conversational Analytics: Use conversational interfaces to analyze your business data. Natural Language Processing is there to help you with voice data and more. Automated analysis of reviews and suggestions.

Customer Service

Social Listening & Ticketing: Leverage Natural Language Processing and machine vision to identify customers to contact and respond to them automatically or assign them to relevant agents increasing customer satisfaction. Use the data available in social networks to uncover who to sell and what to sell.

Intelligent Call Routing: Route calls to most capable agent available. Intelligent routing systems incorporate data from all customer interactions optimizing customer satisfaction. Based on the customer profile and your agent’s performance make it possible to provide the right service with the right agent. Reach superior net promoter scores.

Call Classification: Leverage Natural Language Processing to understand what customer is trying to achieve enabling your agents to focus on higher value-added activities. Before channeling the call, detect the nature of your customers’ needs and let the right department handle the problem. Enhancing efficiency with higher satisfaction rates.

Voice Authentication: Authenticate customers without passwords leveraging biometry to improve customer satisfaction and reduce issues related to forgotten passwords. Their unique voice id will be their most secure key for accessing confidential information. Instead of last four digits of SSN, customers will gain access by using their own voice.

Customer Service Response Suggestions: Bots will listen in on agents’ calls suggesting best practice answers to improve customer satisfaction and standardize customer experience. Increase upsells and cross-sells by giving the right suggestion. Responses will be standardized, and best possible approach will serve the benefit of the customer.

Customer Service Chatbot (Self – Service Solution): Build your own 24/7 functioning, intelligent, self-improving chatbots to handle most queries and transfer customers to live agents when needed. Reduce customer service costs and increase customer satisfaction. Reduce the traffic on your existing customer representatives and make them focus on more specific needs of your customer.

Survey & Review Analytics: Leverage Natural Language Processing to analyze text fields in surveys and reviews to uncover insights to improve customer satisfaction and increase efficiency. Automate the process by mapping the right keywords with right scores. Making it possible to lower the time for generating reports.

Chatbot Analytics: Analyze how customers are interacting with your chatbot. See the overall performance of your chatbot. Pinpoint its shortcomings and improve your chatbot. Detect the overall satisfaction rate of your customer with the chatbot.

Data

Data Integration: Combine your data from different sources into meaningful and valuable information. Data traffic depends on multiple platforms. Therefore, managing this huge traffic and structuring the data into meaningful format will be important. Keep your data lake available for further analysis.

Data Preparation Platform: Prepare your data from raw formats with data quality problems to a clean, ready to analyze format. Use extract, transform and load (ETL) platforms to fine tune your data before placing it into a data warehouse.

Data Cleaning & Validation Platform: Avoid garbage in, garbage out by ensuring the quality of your data with appropriate data cleaning processes and tools. Automate the validation process by using external data sources. Regular maintenance cleaning can be scheduled, and quality of the data can be increased.

Data Transformation: Transform your data to prepare it for advanced analytics. If it is unstructured adjust it for the required format.

Appdev: App development platforms for your custom projects. Your in-house development team can create original projects for your specific business needs. These platforms will help your team with the necessary tools.

Expense Reporting: Use machine learning to improve basic business accounting, including expense reporting. Reduce approval workflows and processing cost for per unit.

Credit Lending & Scoring: Use AI for robust credit lending applications. Use predictive models to uncover the potentially non-performing loans and act. See the potential credit scores of your customers before they apply for a loan and provide custom tailored plans.

Robo-Advisory: Use AI chatbot and mobile app assistant applications to monitor personal finances. Set your target savings or spending rates for your own goals. Your own finance assistant will handle the rest and provide you with insights to reach financial targets.

Regulatory Compliance: Use Natural Language Processing to quickly scan legal and regulatory text for compliance issues, and do so at scale. Handle thousands of paperwork, without any human interaction.

Data Gathering: Use AI to efficiently gather external data such as sentiment and other market-related data. Wrangle data for your financial models and trading approaches.

HealthTech

Patient Data Analytics: Analyze patient and/or 3rd party data to discover insights and suggest actions. Greater accuracy by assisted diagnostics. Lower the mortality rates and increase the patient satisfaction by using all the diagnostic data available to detect the underlying reasons for the symptoms.

Personalized Medications and Care: Find the best treatment plans according to patient data. Provide custom-tailored solutions for your patients. By using their medical history, genetic profile, you can create a custom medication or care plan.

Drug Discovery: Find new drugs based on previous data and medical intelligence. Lower your R&D cost and increase the output. All leading to greater efficiency. Integrate FDA data and you can transform your drug discovery by locating market mismatches and FDA approval or rejection rates.

Early Diagnosis: Analyze chronic conditions leveraging lab data and other medical data to enable early diagnosis. Provide a detailed report on the likelihood of development of certain diseases with genetic data. Integrate the right care plan for eliminating or reducing the risk factors.

Assisted or Automated Diagnosis & Prescription: Suggest the best treatment based on the patient complaint and other data. Put in place control mechanisms that detect and prevent possible diagnosis errors. Find out which active compound is most effective against that specific patient. Get the right statistics for a superior care management.

Pregnancy Management: Monitor mother and fetus health to reduce mothers’ worries and enable early diagnosis. Use machine learning to quickly uncover potential risks and complications. Lower the rates of miscarriage and pregnancy-related diseases.

Healthcare Market Research: Prepare hospital competitive intelligence by tracking the market prices. See the available insurance plans, drug prices, and many more public data to optimize your services. Leverage NLP tools to analyze the vast size of unstructured data.

Healthcare Brand Management and Marketing: Create an optimal marketing strategy for the brand based on market perception and target segment. Tools that offer high granularity will allow you to reach the specific target and increase your sales.

Gene Analytics and Editing: Understand gene and its component. Predict the impact of gene edits. Before using gene therapy, use models the uncover what are the possible outcomes and find are the other solutions.

Device and Drug Comparative Effectiveness: Analyze drug and medical device effectiveness. Rather than just using simulations, test on other patient’s data to see the effectiveness of the new drug, compare your results with benchmark drugs to make an impact with the drug.

HR

Hiring: Hiring is a prediction game: Which candidate, starting at a specific position, will contribute more to the company? Machine’s better data processing capabilities augment HR employees in various parts of hiring such as finding qualified candidates, interviewing them with bots to understand their fit or evaluating their assessment results to decide if they should receive an offer

HR Retention Management: Predict which employees are likely to churn and improve their job satisfaction to retain them. Detect the underlying reasons for their motive for seeking new opportunities. By keeping them at your organization, lower your human capital loss.

HR Analytics: HR analytics services is like the voice of employee analysis. See your people analytics and make better people decisions. Gain actionable insights and impactful suggestions for higher employee satisfaction.

Digital Assistant: Digital assistants are mature enough to replace real assistants in email communication. Include them in your emails to schedule meetings. They have already scheduled hundreds of thousands of meetings. Use the power of artificial intelligence in your day to day activities. Your own on-demand powerful AI backed assistant helping you 24/7.

Employee Monitoring: Monitor your employees for better productivity measurement. Provide objective metrics to see how well they function. Forecast their overall performance with the availability of massive amounts of data.

Building Management: Sensors and advanced analytics improve building management. Integrate IoT systems in your building for lower energy consumption and many more. Increase the available data by implementing the right data collection tools for a effective building management.

IT

Analytics & Predictive Intelligence for Security: Analyze data feeds about the broad cyber activity as well as behavioral data inside an organization’s network to come up with actionable insights to help analysts predict and thwart impending attacks. Integrate external data sources the watch out for global cyber threats and act timely. Keep your IT infrastructure intact or minimize losses.

Deception Security: Deploy decoy-assets in a network as bait for attackers, to identify, track, and disrupt security threats such as advanced automated malware attacks before they inflict damage. Keep your data and traffic safe by keeping them engaged in decoys. Enhance your cybersecurity capabilities against various forms of cyber attacks

Autonomous Cybersecurity Systems: Utilize learning systems to efficiently and instantaneously respond to security threats, often augmenting the work of security analysts. Lower your risk of human errors by providing greater autonomy for your cybersecurity. AI backed systems can check the compliance with standards.

AI Developer: Develop your custom AI solutions with companies experienced in AI development. Create turnkey projects and deploy them to the specific business function. Best for companies with limited in-house capabilities for artificial intelligence.

Developer Assistance: Assist your developers using AI to help them intelligently access the coding knowledge on the web and learn from suggested code samples. See the best practices for specific development task and formulate your custom solution. Real-time feedback provided by the huge history of developer mistakes and best practices.

AI Consultancy: Provides consultancy services to support your in-house AI development including machine learning and data science projects. See which units can benefit most from AI deployment. Optimize your artificial intelligence spending for best results from the insight provided by a consultant.

Operations

Robotic Process Automation (RPA): Digitize your processes in weeks without replacing legacy systems which can take years. Bots can operate on legacy systems learning from your personnel’s instructions and actions. Increase your efficiency and profitability ratios. Increase speed and precision and many more.

Manufacturing Analytics: Also called industrial analytics systems, these systems allow you to analyze your manufacturing process from production to logistics to save time, reduce cost and increase efficiency. Keep your industry effectiveness at optimal levels.

Robotics: Factory floors are changing with programmable collaborative bots that can work next to employees to take over more repetitive tasks. Automate physical processes such as manufacturing or logistics with the help of advanced robotics. Increased your connected systems by centralizing the whole manufacturing process. Lower your exposures to human errors.

Robotic Process Automation (RPA) Implementation: Implementing RPA solutions requires effort. Suitable processes need to be identified. If a rules-based robot will be used, the robot needs to be programmed. Employees’ questions need to be answered. That is why most companies get some level of external help. Generally, outsourcing companies, consultants, and IT integrators are happy to provide the temporary labor to undertake this effort.

Cashierless Checkout: Self-checkout systems have many names. They are called cashierless, cashier-free or automated checkout systems. They allow retail companies to serve customers in their physical stores without the need for cashiers. Technologies that allowed users to scan and pay for their products have been used for almost a decade now and those systems did not require great advances in AI. However, these days we are witnessing systems powered by advanced sensors and AI to identify purchased merchandise and charge customers automatically.

Self-Driving Cars

Self-Driving Cars: From mining to manufacturing, self-driving cars/vehicles are increasing efficiency and effectiveness of operations. Integrate them into your business for greater efficiency. Leverage the power of artificial intelligence for complex tasks.

AppliedAI

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